Differential transcript usage analysis of bulk and single-cell RNA-seq data with DTUrtle

Single-Cell Omics for Transcriptome CHaracterization (SCOTCH): isoform-level characterization of gene expression through long-read single-cell RNA sequencing

Recent development involving long-read single-cell transcriptome sequencing (lr-scRNA-Seq) represents a significant leap forward in single-cell genomics. With the recent introduction of R10 flowcells by Oxford Nanopore, we propose that previous computational methods designed to handle high sequencing error rates are less relevant, and that the traditional approach using short reads to compile "barcode space" (candidate barcode list) to de-multiplex long reads are no longer necessary. Instead, computational methods should now shift focus on harnessing the unique benefits of long reads to analyze transcriptome complexity. In this context, we introduce a comprehensive suite of computational methods named Single-Cell Omics for Transcriptome CHaracterization (SCOTCH). SCOTCH supports both Nanopore and PacBio sequencing platforms, and is compatible with single-cell library preparation protocols from both 10X Genomics and Parse Biosciences. Through a sub-exon identification strategy with dynamic thresholding and read mapping scores, SCOTCH precisely aligns reads to known isoforms and discover novel isoforms, efficiently addressing ambiguous mapping challenges commonly encountered in long-read single-cell data. Comprehensive simulations and real data analyses across multiple platforms (including 10X Genomics and Parse Bioscience, paired with Illumina or Nanopore sequencing technologies with R9 and R10 flowcells, as well as PacBio sequencing) demonstrated that SCOTCH outperforms existing methods in mapping accuracy, quantification accuracy and novel isoform detection, while also uncovering novel biological insights on transcriptome complexity at the single-cell level.

Tracing ALS Degeneration: Insights from Spinal Cord and Cortex Transcriptomes

BACKGROUND/OBJECTIVES

Amyotrophic Lateral Sclerosis is a progressive neurodegenerative disorder characterized by the loss of upper and lower motor neurons. Key factors contributing to neuronal death include mitochondrial energy damage, oxidative stress, and excitotoxicity. The frontal cortex is crucial for action initiation, planning, and voluntary movements whereas the spinal cord facilitates communication with the brain, walking, and reflexes. By investigating transcriptome data from the frontal cortex and spinal cord, we aim to elucidate common pathological mechanisms and pathways involved in ALS for understanding the disease progression and identifying potential therapeutic targets.

METHODS

In this study, we quantified gene and transcript expression patterns, predicted variants, and assessed their functional effects using computational tools. It also includes predicting variant-associated regulatory effects, constructing functional interaction networks, and performing a gene enrichment analysis.

RESULTS

We found novel genes for the upregulation of immune response, and the downregulation of metabolic-related and defective degradation processes in both the spinal cord and frontal cortex. Additionally, we observed the dysregulation of histone regulation and blood pressure-related genes specifically in the frontal cortex.

CONCLUSIONS

These results highlight the distinct and shared molecular disruptions in ALS, emphasizing the critical roles of immune response and metabolic dysfunction in neuronal degeneration. Targeting these pathways may provide new therapeutic avenues to combat neurodegeneration and preserve neuronal health.

Dynamic landscape of m6A modifications and related post-transcriptional events in muscle-invasive bladder cancer

BACKGROUND

Muscle-invasive bladder carcinoma (MIBC) is a serious and more advanced stage of bladder carcinoma. N6-Methyladenosine (m6A) is a dynamic and reversible modifications that primarily affects RNA stability and alternative splicing. The dysregulation of m6A in MIBC can be potential target for clinical interventions, but there have been limited studies on m6A modifications in MIBC and their associations with post-transcriptional regulatory processes.

METHODS

Paired tumor and adjacent-normal tissues were obtained from three patients with MIBC following radical cystectomy. The additional paired tissues for validation were obtained from patients underwent transurethral resection. Utilizing Nanopore direct-RNA sequencing, we characterized the m6A RNA methylation landscape in MIBC, with a focus on identifying post-transcriptional events potentially affected by changes in m6A sites. This included an examination of differential transcript usage, polyadenylation signal sites, and variations in poly(A) tail length, providing insights into the broader impact of m6A alterations on RNA processing in MIBC.

RESULTS

The prognostic-related m6A genes and m6A-risk model constructed by machine learning enables the stratification of high and low-risk patients with precision. A novel m6A modification site in the 3' untranslated region (3'UTR) of IGLL5 gene were identified, characterized by a lower m6A methylation ratio, elongated poly(A) tails, and a notable bias in transcript usage. Furthermore, we discovered two particular transcripts, VWA1-203 and CEBPB-201. VWA1-203 displayed diminished m6A methylation levels, a truncated 3'UTR, and an elongated poly(A) tail, whereas CEBPB-201 showed opposite trends, highlighting the complex interplay between m6A modifications and RNA processing. Source code was provided on GitHub ( https://github.com/lelelililele/Nanopore-m6A-analysis ).

CONCLUSIONS

The state-of-the-art Nanopore direct-RNA sequencing and machine learning techniques enables comprehensive identification of m6A modification and provided insights into the potential post-transcriptional regulation mechanisms on the development and progression in MIBC.

Unique Splicing of Lrp5 in the Brain: A New Player in Neurodevelopment and Brain Maturation

Low-density lipoprotein receptor-related protein 5 (LRP5) is a constitutively expressed receptor with observed roles in bone homeostasis, retinal development, and cardiac metabolism. However, the function of LRP5 in the brain remains unexplored. This study investigates LRP5's role in the central nervous system by conducting an extensive analysis using RNA-seq tools and in silico assessments. Two protein-coding Lrp5 transcripts are expressed in mice: full-length Lrp5-201 and a truncated form encoded by Lrp5-202. Wt mice express Lrp5-201 in the liver and brain and do not express the truncated form. Lrp5-/- mice express Lrp5-202 in the liver and brain and do not express Lrp5-201 in the liver. Interestingly, Lrp5-/- mouse brains show full-length Lrp5-201 expression, suggesting that LRP5 has a role in preserving brain function during development. Functional gene enrichment analysis on RNA-seq unveils dysregulated expression of genes associated with neuronal differentiation and synapse formation in the brains of Lrp5-/- mice compared to Wt mice. Furthermore, Gene Set Enrichment Analysis highlights downregulated expression of genes involved in retinol and linoleic acid metabolism in Lrp5-/- mouse brains. Tissue-specific alternative splicing of Lrp5 in Lrp5-/- mice supports that the expression of LRP5 in the brain is needed for the correct synthesis of vitamins and fatty acids, and it is indispensable for correct brain development.

Quantifying transcriptome diversity: a review

Following the central dogma of molecular biology, gene expression heterogeneity can aid in predicting and explaining the wide variety of protein products, functions and, ultimately, heterogeneity in phenotypes. There is currently overlapping terminology used to describe the types of diversity in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptome diversity as a measure of the heterogeneity in (1) the expression of all genes within a sample or a single gene across samples in a population (gene-level diversity) or (2) the isoform-specific expression of a given gene (isoform-level diversity). We first overview modulators and quantification of transcriptome diversity at the gene level. Then, we discuss the role alternative splicing plays in driving transcript isoform-level diversity and how it can be quantified. Additionally, we overview computational resources for calculating gene-level and isoform-level diversity for high-throughput sequencing data. Finally, we discuss future applications of transcriptome diversity. This review provides a comprehensive overview of how gene expression diversity arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms and species.

Comprehensive benchmark of differential transcript usage analysis for static and dynamic conditions

RNA sequencing offers unique insights into transcriptome diversity, and a plethora of tools have been developed to analyze alternative splicing. One important task is to detect changes in the relative transcript abundance in differential transcript usage (DTU) analysis. The choice of the right analysis tool is non-trivial and depends on experimental factors such as the availability of single- or paired-end and bulk or single-cell data. To help users select the most promising tool for their task, we performed a comprehensive benchmark of DTU detection tools. We cover a wide array of experimental settings, using simulated bulk and single-cell RNA-seq data as well as real transcriptomics datasets, including time-series data. Our results suggest that DEXSeq, edgeR, and LimmaDS are better choices for paired-end data, while DSGseq and DEXSeq can be used for single-end data. In single-cell simulation settings, we showed that satuRn performs better than DTUrtle. In addition, we showed that Spycone is optimal for time series DTU/IS analysis based on the evidence provided using GO terms enrichment analysis.

Analyzing alternative splicing in Alzheimer's disease postmortem brain: a cell-level perspective

Alzheimer's disease (AD) is a neurodegenerative disease with no effective cure that attacks the brain's cells resulting in memory loss and changes in behavior and language skills. Alternative splicing is a highly regulated process influenced by specific cell types and has been implicated in age-related disorders such as neurodegenerative diseases. A comprehensive detection of alternative splicing events (ASEs) at the cellular level in postmortem brain tissue can provide valuable insights into AD pathology. Here, we provided cell-level ASEs in postmortem brain tissue by employing bioinformatics pipelines on a bulk RNA sequencing study sorted by cell types and two single-cell RNA sequencing studies from the prefrontal cortex. This comprehensive analysis revealed previously overlooked splicing and expression changes in AD patient brains. Among the observed alterations were changed in the splicing and expression of transcripts associated with chaperones, including CLU in astrocytes and excitatory neurons, PTGDS in astrocytes and endothelial cells, and HSP90AA1 in microglia and tauopathy-afflicted neurons, which were associated with differential expression of the splicing factor DDX5. In addition, novel, unknown transcripts were altered, and structural changes were observed in lncRNAs such as MEG3 in neurons. This work provides a novel strategy to identify the notable ASEs at the cell level in neurodegeneration, which revealed cell type-specific splicing changes in AD. This finding may contribute to interpreting associations between splicing and neurodegenerative disease outcomes.

Investigating Neuron Degeneration in Huntington's Disease Using RNA-Seq Based Transcriptome Study

Huntington's disease (HD) is a progressive neurodegenerative disorder caused due to a CAG repeat expansion in the huntingtin (HTT) gene. The primary symptoms of HD include motor dysfunction such as chorea, dystonia, and involuntary movements. The primary motor cortex (BA4) is the key brain region responsible for executing motor/movement activities. Investigating patient and control samples from the BA4 region will provide a deeper understanding of the genes responsible for neuron degeneration and help to identify potential markers. Previous studies have focused on overall differential gene expression and associated biological functions. In this study, we illustrate the relationship between variants and differentially expressed genes/transcripts. We identified variants and their associated genes along with the quantification of genes and transcripts. We also predicted the effect of variants on various regulatory activities and found that many variants are regulating gene expression. Variants affecting miRNA and its targets are also highlighted in our study. Co-expression network studies revealed the role of novel genes. Function interaction network analysis unveiled the importance of genes involved in vesicle-mediated transport. From this unified approach, we propose that genes expressed in immune cells are crucial for reducing neuron death in HD.

Mutations in DARS2 result in global dysregulation of mRNA metabolism and splicing

Leukoencephalopathy with brainstem and spinal cord involvement and lactate elevation (LBSL) is a rare neurological disorder caused by the mutations in the DARS2 gene, which encodes the mitochondrial aspartyl-tRNA synthetase. The objective of this study was to understand the impact of DARS2 mutations on cell processes through evaluation of LBSL patient stem cell derived cerebral organoids and neurons. We generated human cerebral organoids (hCOs) from induced pluripotent stem cells (iPSCs) of seven LBSL patients and three healthy controls using an unguided protocol. Single cells from 70-day-old hCOs were subjected to SMART-seq2 sequencing and bioinformatic analysis to acquire high-resolution gene and transcript expression datasets. Global gene expression analysis demonstrated dysregulation of a number of genes involved in mRNA metabolism and splicing processes within LBSL hCOs. Importantly, there were distinct and divergent gene expression profiles based on the nature of the DARS2 mutation. At the transcript level, pervasive differential transcript usage and differential spliced exon events that are involved in protein translation and metabolism were identified in LBSL hCOs. Single-cell analysis of DARS2 (exon 3) showed that some LBSL cells exclusively express transcripts lacking exon 3, indicating that not all LBSL cells can benefit from the "leaky" nature common to splice site mutations. At the gene- and transcript-level, we uncovered that dysregulated RNA splicing, protein translation and metabolism may underlie at least some of the pathophysiological mechanisms in LBSL. To confirm hCO findings, iPSC-derived neurons (iNs) were generated by overexpressing Neurogenin 2 using lentiviral vector to study neuronal growth, splicing of DARS2 exon 3 and DARS2 protein expression. Live cell imaging revealed neuronal growth defects of LBSL iNs, which was consistent with the finding of downregulated expression of genes related to neuronal differentiation in LBSL hCOs. DARS2 protein was downregulated in iNs compared to iPSCs, caused by increased exclusion of exon 3. The scope and complexity of our data imply that DARS2 is potentially involved in transcription regulation beyond its canonical role of aminoacylation. Nevertheless, our work highlights transcript-level dysregulation as a critical, and relatively unexplored, mechanism linking genetic data with neurodegenerative disorders.

Quantitative Analysis of Isoform Switching in Cancer

Over the past 8 years, multiple studies examined the phenomenon of isoform switching in human cancers and discovered that isoform switching is widespread, with hundreds to thousands of such events per cancer type. Although all of these studies used slightly different definitions of isoform switching, which in part led to a rather poor overlap of their results, they all leveraged transcript usage, a proportion of the transcript's expression in the total expression level of the parent gene, to detect isoform switching. However, how changes in transcript usage correlate with changes in transcript expression is not sufficiently explored. In this article, we adopt the most common definition of isoform switching and use a state-of-the-art tool for the analysis of differential transcript usage, SatuRn, to detect isoform switching events in 12 cancer types. We analyze the detected events in terms of changes in transcript usage and the relationship between transcript usage and transcript expression on a global scale. The results of our analysis suggest that the relationship between changes in transcript usage and changes in transcript expression is far from straightforward, and that such quantitative information can be effectively used for prioritizing isoform switching events for downstream analyses.

Mutations in DARS2 result in global dysregulation of mRNA metabolism and splicing

Leukoencephalopathy with brain stem and spinal cord involvement and lactate elevation (LBSL) is a rare neurological disorder caused by the mutations in the DARS2 gene, which encodes the mitochondrial aspartyl-tRNA synthetase. The objective of this study was to understand the impact of DARS2 mutations on cell processes through evaluation of LBSL patient stem cell derived cerebral organoids and neurons. We generated human cerebral organoids (hCOs) from induced pluripotent stem cells (iPSCs) of seven LBSL patients and three healthy controls using an unguided protocol. Single cells from 70-day-old hCOs underwent SMART-seq2 sequencing and multiple bioinformatic analysis tools were applied to high-resolution gene and transcript expression analyses. To confirm hCO findings, iPSC-derived neurons (iNs) were generated by overexpressing Neurogenin 2 using lentiviral vector to study neuronal growth, splicing of DARS2 exon 3 and DARS2 protein expression. Global gene expression analysis demonstrated dysregulation of a number of genes involved in mRNA metabolism and splicing processes within LBSL hCOs. Importantly, there were distinct and divergent gene expression profiles based on the nature of the DARS2 mutation. At the transcript level, pervasive differential transcript usage and differential spliced exon events that are involved in protein translation and metabolism were identified in LBSL hCOs. Single-cell analysis of DARS2 (exon 3) showed that some LBSL cells exclusively express transcripts lacking exon 3, indicating that not all LBSL cells can benefit from the "leaky" nature common to splice site mutations. Live cell imaging revealed neuronal growth defects of LBSL iNs, which was consistent with the finding of downregulated expression of genes related to neuronal differentiation in LBSL hCOs. DARS2 protein was downregulated in iNs compared to iPSCs, caused by increased exclusion of exon 3. At the gene- and transcript-level, we uncovered that dysregulated RNA splicing, protein translation and metabolism may underlie at least some of the pathophysiological mechanisms in LBSL. The scope and complexity of our data imply that DARS2 is potentially involved in transcription regulation beyond its canonical role of aminoacylation. Nevertheless, our work highlights transcript-level dysregulation as a critical, and relatively unexplored, mechanism linking genetic data with neurodegenerative disorders.

Transcriptome analyses in infertile men reveal germ cell-specific expression and splicing patterns

The process of spermatogenesis-when germ cells differentiate into sperm-is tightly regulated, and misregulation in gene expression is likely to be involved in the physiopathology of male infertility. The testis is one of the most transcriptionally rich tissues; nevertheless, the specific gene expression changes occurring during spermatogenesis are not fully understood. To better understand gene expression during spermatogenesis, we generated germ cell-specific whole transcriptome profiles by systematically comparing testicular transcriptomes from tissues in which spermatogenesis is arrested at successive steps of germ cell differentiation. In these comparisons, we found thousands of differentially expressed genes between successive germ cell types of infertility patients. We demonstrate our analyses' potential to identify novel highly germ cell-specific markers (TSPY4 and LUZP4 for spermatogonia; HMGB4 for round spermatids) and identified putatively misregulated genes in male infertility (RWDD2A, CCDC183, CNNM1, SERF1B). Apart from these, we found thousands of genes showing germ cell-specific isoforms (including SOX15, SPATA4, SYCP3, MKI67). Our approach and dataset can help elucidate genetic and transcriptional causes for male infertility.

Robust and annotation-free analysis of alternative splicing across diverse cell types in mice

Although alternative splicing is a fundamental and pervasive aspect of gene expression in higher eukaryotes, it is often omitted from single-cell studies due to quantification challenges inherent to commonly used short-read sequencing technologies. Here, we undertake the analysis of alternative splicing across numerous diverse murine cell types from two large-scale single-cell datasets-the Tabula Muris and BRAIN Initiative Cell Census Network-while accounting for understudied technical artifacts and unannotated events. We find strong and general cell-type-specific alternative splicing, complementary to total gene expression but of similar discriminatory value, and identify a large volume of novel splicing events. We specifically highlight splicing variation across different cell types in primary motor cortex neurons, bone marrow B cells, and various epithelial cells, and we show that the implicated transcripts include many genes which do not display total expression differences. To elucidate the regulation of alternative splicing, we build a custom predictive model based on splicing factor activity, recovering several known interactions while generating new hypotheses, including potential regulatory roles for novel alternative splicing events in critical genes like Khdrbs3 and Rbfox1. We make our results available using public interactive browsers to spur further exploration by the community.